Overview

Dataset statistics

Number of variables34
Number of observations14385
Missing cells65837
Missing cells (%)13.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory272.0 B

Variable types

Text10
Categorical17
Numeric7

Alerts

OverallSideCrashRating is highly imbalanced (54.2%)Imbalance
SideCrashPassengersideRating is highly imbalanced (52.0%)Imbalance
combinedSideBarrierAndPoleRating-Front is highly imbalanced (56.8%)Imbalance
combinedSideBarrierAndPoleRating-Rear is highly imbalanced (61.9%)Imbalance
sideBarrierRating-Overall is highly imbalanced (54.5%)Imbalance
RolloverRating2 is highly imbalanced (78.3%)Imbalance
SidePoleCrashRating is highly imbalanced (54.4%)Imbalance
NHTSAElectronicStabilityControl is highly imbalanced (53.6%)Imbalance
VehiclePicture has 4544 (31.6%) missing valuesMissing
FrontCrashPicture has 9563 (66.5%) missing valuesMissing
FrontCrashVideo has 10202 (70.9%) missing valuesMissing
SideCrashVideo has 10339 (71.9%) missing valuesMissing
SideCrashPicture has 9757 (67.8%) missing valuesMissing
SidePolePicture has 10642 (74.0%) missing valuesMissing
SidePoleVideo has 10790 (75.0%) missing valuesMissing
VehicleId has unique valuesUnique
RolloverPossibility has 7860 (54.6%) zerosZeros
RolloverPossibility2 has 13581 (94.4%) zerosZeros
ComplaintsCount has 2645 (18.4%) zerosZeros
RecallsCount has 3154 (21.9%) zerosZeros
InvestigationCount has 8395 (58.4%) zerosZeros

Reproduction

Analysis started2024-10-29 14:14:40.493871
Analysis finished2024-10-29 14:14:45.024510
Duration4.53 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

VehiclePicture
Text

MISSING 

Distinct5156
Distinct (%)52.4%
Missing4544
Missing (%)31.6%
Memory size112.5 KiB
2024-10-29T15:14:45.116281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length61
Mean length60.744741
Min length60

Characters and Unicode

Total characters597789
Distinct characters55
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2657 ?
Unique (%)27.0%

Sample

1st rowhttps://static.nhtsa.gov/images/vehicles/4447_st0640_046.png
2nd rowhttps://static.nhtsa.gov/images/vehicles/4637_st0640_046.png
3rd rowhttps://static.nhtsa.gov/images/vehicles/5066_st0640_046.png
4th rowhttps://static.nhtsa.gov/images/vehicles/4638_st0640_046.png
5th rowhttps://static.nhtsa.gov/images/vehicles/5064_st0640_046.png
ValueCountFrequency (%)
https://static.nhtsa.gov/images/vehicles/12832_st0640_046.png 38
 
0.4%
https://static.nhtsa.gov/images/vehicles/11236_st0640_046.png 23
 
0.2%
https://static.nhtsa.gov/images/vehicles/12066_st0640_046.png 20
 
0.2%
https://static.nhtsa.gov/images/vehicles/11809_st0640_046.png 20
 
0.2%
https://static.nhtsa.gov/images/vehicles/13993_st0640_046.png 16
 
0.2%
https://static.nhtsa.gov/images/vehicles/12213_st0640_046.png 16
 
0.2%
https://static.nhtsa.gov/images/vehicles/11190_st0640_046.png 15
 
0.2%
https://static.nhtsa.gov/images/vehicles/13789_st0640_046.png 14
 
0.1%
https://static.nhtsa.gov/images/vehicles/10692_st0640_046.png 14
 
0.1%
https://static.nhtsa.gov/images/vehicles/15016_st0640_046.png 14
 
0.1%
Other values (5146) 9651
98.1%
2024-10-29T15:14:45.312727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 58740
 
9.8%
t 58740
 
9.8%
/ 49205
 
8.2%
0 33987
 
5.7%
h 29523
 
4.9%
g 29523
 
4.9%
a 29523
 
4.9%
i 29523
 
4.9%
e 29523
 
4.9%
. 29523
 
4.9%
Other values (45) 219979
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 373958
62.6%
Decimal Number 114081
 
19.1%
Other Punctuation 88569
 
14.8%
Connector Punctuation 20139
 
3.4%
Uppercase Letter 1042
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 186
17.9%
T 174
16.7%
B 170
16.3%
G 77
 
7.4%
D 54
 
5.2%
K 42
 
4.0%
S 41
 
3.9%
A 34
 
3.3%
X 34
 
3.3%
M 32
 
3.1%
Other values (16) 198
19.0%
Lowercase Letter
ValueCountFrequency (%)
s 58740
15.7%
t 58740
15.7%
h 29523
7.9%
g 29523
7.9%
a 29523
7.9%
i 29523
7.9%
e 29523
7.9%
c 20294
 
5.4%
v 19682
 
5.3%
p 19682
 
5.3%
Other values (5) 49205
13.2%
Decimal Number
ValueCountFrequency (%)
0 33987
29.8%
4 23506
20.6%
6 22868
20.0%
1 9127
 
8.0%
3 4511
 
4.0%
2 4363
 
3.8%
5 4138
 
3.6%
8 3994
 
3.5%
9 3861
 
3.4%
7 3726
 
3.3%
Other Punctuation
ValueCountFrequency (%)
/ 49205
55.6%
. 29523
33.3%
: 9841
 
11.1%
Connector Punctuation
ValueCountFrequency (%)
_ 20139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 375000
62.7%
Common 222789
37.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 58740
15.7%
t 58740
15.7%
h 29523
7.9%
g 29523
7.9%
a 29523
7.9%
i 29523
7.9%
e 29523
7.9%
c 20294
 
5.4%
v 19682
 
5.2%
p 19682
 
5.2%
Other values (31) 50247
13.4%
Common
ValueCountFrequency (%)
/ 49205
22.1%
0 33987
15.3%
. 29523
13.3%
4 23506
10.6%
6 22868
10.3%
_ 20139
9.0%
: 9841
 
4.4%
1 9127
 
4.1%
3 4511
 
2.0%
2 4363
 
2.0%
Other values (4) 15719
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 597789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 58740
 
9.8%
t 58740
 
9.8%
/ 49205
 
8.2%
0 33987
 
5.7%
h 29523
 
4.9%
g 29523
 
4.9%
a 29523
 
4.9%
i 29523
 
4.9%
e 29523
 
4.9%
. 29523
 
4.9%
Other values (45) 219979
36.8%

OverallRating
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9556 
5
3080 
4
1641 
3
 
88
2
 
20

Length

Max length9
Median length9
Mean length6.3144247
Min length1

Characters and Unicode

Total characters90833
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9556
66.4%
5 3080
 
21.4%
4 1641
 
11.4%
3 88
 
0.6%
2 20
 
0.1%

Length

2024-10-29T15:14:45.403151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:45.466539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9556
39.9%
rated 9556
39.9%
5 3080
 
12.9%
4 1641
 
6.9%
3 88
 
0.4%
2 20
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t 19112
21.0%
N 9556
10.5%
o 9556
10.5%
9556
10.5%
R 9556
10.5%
a 9556
10.5%
e 9556
10.5%
d 9556
10.5%
5 3080
 
3.4%
4 1641
 
1.8%
Other values (2) 108
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57336
63.1%
Uppercase Letter 19112
 
21.0%
Space Separator 9556
 
10.5%
Decimal Number 4829
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 19112
33.3%
o 9556
16.7%
a 9556
16.7%
e 9556
16.7%
d 9556
16.7%
Decimal Number
ValueCountFrequency (%)
5 3080
63.8%
4 1641
34.0%
3 88
 
1.8%
2 20
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 9556
50.0%
R 9556
50.0%
Space Separator
ValueCountFrequency (%)
9556
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 76448
84.2%
Common 14385
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 19112
25.0%
N 9556
12.5%
o 9556
12.5%
R 9556
12.5%
a 9556
12.5%
e 9556
12.5%
d 9556
12.5%
Common
ValueCountFrequency (%)
9556
66.4%
5 3080
 
21.4%
4 1641
 
11.4%
3 88
 
0.6%
2 20
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 19112
21.0%
N 9556
10.5%
o 9556
10.5%
9556
10.5%
R 9556
10.5%
a 9556
10.5%
e 9556
10.5%
d 9556
10.5%
5 3080
 
3.4%
4 1641
 
1.8%
Other values (2) 108
 
0.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9232 
4
2863 
5
1982 
3
 
276
2
 
32

Length

Max length9
Median length9
Mean length6.1342371
Min length1

Characters and Unicode

Total characters88241
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9232
64.2%
4 2863
 
19.9%
5 1982
 
13.8%
3 276
 
1.9%
2 32
 
0.2%

Length

2024-10-29T15:14:45.531995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:45.589914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9232
39.1%
rated 9232
39.1%
4 2863
 
12.1%
5 1982
 
8.4%
3 276
 
1.2%
2 32
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t 18464
20.9%
N 9232
10.5%
o 9232
10.5%
9232
10.5%
R 9232
10.5%
a 9232
10.5%
e 9232
10.5%
d 9232
10.5%
4 2863
 
3.2%
5 1982
 
2.2%
Other values (2) 308
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55392
62.8%
Uppercase Letter 18464
 
20.9%
Space Separator 9232
 
10.5%
Decimal Number 5153
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 18464
33.3%
o 9232
16.7%
a 9232
16.7%
e 9232
16.7%
d 9232
16.7%
Decimal Number
ValueCountFrequency (%)
4 2863
55.6%
5 1982
38.5%
3 276
 
5.4%
2 32
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
N 9232
50.0%
R 9232
50.0%
Space Separator
ValueCountFrequency (%)
9232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73856
83.7%
Common 14385
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 18464
25.0%
N 9232
12.5%
o 9232
12.5%
R 9232
12.5%
a 9232
12.5%
e 9232
12.5%
d 9232
12.5%
Common
ValueCountFrequency (%)
9232
64.2%
4 2863
 
19.9%
5 1982
 
13.8%
3 276
 
1.9%
2 32
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 18464
20.9%
N 9232
10.5%
o 9232
10.5%
9232
10.5%
R 9232
10.5%
a 9232
10.5%
e 9232
10.5%
d 9232
10.5%
4 2863
 
3.2%
5 1982
 
2.2%
Other values (2) 308
 
0.3%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
6554 
5
3661 
4
3376 
3
 
597
2
 
117
Other values (2)
 
80

Length

Max length9
Median length1
Mean length4.6449079
Min length1

Characters and Unicode

Total characters66817
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row4
3rd row5
4th row4
5th row5

Common Values

ValueCountFrequency (%)
Not Rated 6554
45.6%
5 3661
25.5%
4 3376
23.5%
3 597
 
4.2%
2 117
 
0.8%
1 59
 
0.4%
0 21
 
0.1%

Length

2024-10-29T15:14:45.653871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:45.716310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 6554
31.3%
rated 6554
31.3%
5 3661
17.5%
4 3376
16.1%
3 597
 
2.9%
2 117
 
0.6%
1 59
 
0.3%
0 21
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t 13108
19.6%
N 6554
9.8%
o 6554
9.8%
6554
9.8%
R 6554
9.8%
a 6554
9.8%
e 6554
9.8%
d 6554
9.8%
5 3661
 
5.5%
4 3376
 
5.1%
Other values (4) 794
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39324
58.9%
Uppercase Letter 13108
 
19.6%
Decimal Number 7831
 
11.7%
Space Separator 6554
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3661
46.8%
4 3376
43.1%
3 597
 
7.6%
2 117
 
1.5%
1 59
 
0.8%
0 21
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
t 13108
33.3%
o 6554
16.7%
a 6554
16.7%
e 6554
16.7%
d 6554
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 6554
50.0%
R 6554
50.0%
Space Separator
ValueCountFrequency (%)
6554
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52432
78.5%
Common 14385
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 13108
25.0%
N 6554
12.5%
o 6554
12.5%
R 6554
12.5%
a 6554
12.5%
e 6554
12.5%
d 6554
12.5%
Common
ValueCountFrequency (%)
6554
45.6%
5 3661
25.5%
4 3376
23.5%
3 597
 
4.2%
2 117
 
0.8%
1 59
 
0.4%
0 21
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 13108
19.6%
N 6554
9.8%
o 6554
9.8%
6554
9.8%
R 6554
9.8%
a 6554
9.8%
e 6554
9.8%
d 6554
9.8%
5 3661
 
5.5%
4 3376
 
5.1%
Other values (4) 794
 
1.2%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
6557 
4
3850 
5
2933 
3
740 
2
 
176
Other values (2)
 
129

Length

Max length9
Median length1
Mean length4.6465763
Min length1

Characters and Unicode

Total characters66841
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row5
5th row5

Common Values

ValueCountFrequency (%)
Not Rated 6557
45.6%
4 3850
26.8%
5 2933
20.4%
3 740
 
5.1%
2 176
 
1.2%
0 78
 
0.5%
1 51
 
0.4%

Length

2024-10-29T15:14:45.784339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:45.844332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 6557
31.3%
rated 6557
31.3%
4 3850
18.4%
5 2933
14.0%
3 740
 
3.5%
2 176
 
0.8%
0 78
 
0.4%
1 51
 
0.2%

Most occurring characters

ValueCountFrequency (%)
t 13114
19.6%
N 6557
9.8%
o 6557
9.8%
6557
9.8%
R 6557
9.8%
a 6557
9.8%
e 6557
9.8%
d 6557
9.8%
4 3850
 
5.8%
5 2933
 
4.4%
Other values (4) 1045
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39342
58.9%
Uppercase Letter 13114
 
19.6%
Decimal Number 7828
 
11.7%
Space Separator 6557
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 3850
49.2%
5 2933
37.5%
3 740
 
9.5%
2 176
 
2.2%
0 78
 
1.0%
1 51
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
t 13114
33.3%
o 6557
16.7%
a 6557
16.7%
e 6557
16.7%
d 6557
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 6557
50.0%
R 6557
50.0%
Space Separator
ValueCountFrequency (%)
6557
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52456
78.5%
Common 14385
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 13114
25.0%
N 6557
12.5%
o 6557
12.5%
R 6557
12.5%
a 6557
12.5%
e 6557
12.5%
d 6557
12.5%
Common
ValueCountFrequency (%)
6557
45.6%
4 3850
26.8%
5 2933
20.4%
3 740
 
5.1%
2 176
 
1.2%
0 78
 
0.5%
1 51
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66841
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 13114
19.6%
N 6557
9.8%
o 6557
9.8%
6557
9.8%
R 6557
9.8%
a 6557
9.8%
e 6557
9.8%
d 6557
9.8%
4 3850
 
5.8%
5 2933
 
4.4%
Other values (4) 1045
 
1.6%

FrontCrashPicture
Text

MISSING 

Distinct3108
Distinct (%)64.5%
Missing9563
Missing (%)66.5%
Memory size112.5 KiB
2024-10-29T15:14:45.945722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length61
Mean length60.758192
Min length54

Characters and Unicode

Total characters292976
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1725 ?
Unique (%)35.8%

Sample

1st rowhttps://static.nhtsa.gov/crashTest/images/2008/05Matrix-f.jpg
2nd rowhttps://static.nhtsa.gov/crashTest/images/2008/06Prius-f.jpg
3rd rowhttps://static.nhtsa.gov/crashTest/images/2008/06Rav4-f.JPG
4th rowhttps://static.nhtsa.gov/crashTest/images/2008/05Sienna-f.jpg
5th rowhttps://static.nhtsa.gov/crashTest/images/2008/06Tacoma4-f.JPG
ValueCountFrequency (%)
https://static.nhtsa.gov/crashtest/images/2023/v10974p082.jpg 14
 
0.3%
https://static.nhtsa.gov/crashtest/images/2021/v10974p082.jpg 14
 
0.3%
https://static.nhtsa.gov/crashtest/images/2024/v10974p082.jpg 14
 
0.3%
https://static.nhtsa.gov/crashtest/images/2025/v10974p082.jpg 14
 
0.3%
https://static.nhtsa.gov/crashtest/images/2022/v10974p082.jpg 13
 
0.3%
https://static.nhtsa.gov/crashtest/images/2013/v07024p074.jpg 11
 
0.2%
https://static.nhtsa.gov/crashtest/images/2014/v07024p074.jpg 10
 
0.2%
https://static.nhtsa.gov/crashtest/images/2016/v08308p081.jpg 8
 
0.2%
https://static.nhtsa.gov/crashtest/images/2021/v11288p127.jpg 8
 
0.2%
https://static.nhtsa.gov/crashtest/images/2020/v10974p082.jpg 7
 
0.1%
Other values (3098) 4709
97.7%
2024-10-29T15:14:46.135551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 29255
 
10.0%
s 29167
 
10.0%
/ 28932
 
9.9%
a 19997
 
6.8%
0 15213
 
5.2%
h 14537
 
5.0%
. 14467
 
4.9%
g 14264
 
4.9%
e 10188
 
3.5%
i 9990
 
3.4%
Other values (57) 106966
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 182199
62.2%
Decimal Number 51099
 
17.4%
Other Punctuation 48221
 
16.5%
Uppercase Letter 10790
 
3.7%
Dash Punctuation 573
 
0.2%
Connector Punctuation 94
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 29255
16.1%
s 29167
16.0%
a 19997
11.0%
h 14537
8.0%
g 14264
7.8%
e 10188
 
5.6%
i 9990
 
5.5%
c 9869
 
5.4%
p 9392
 
5.2%
v 8724
 
4.8%
Other values (16) 26816
14.7%
Uppercase Letter
ValueCountFrequency (%)
T 4911
45.5%
P 4164
38.6%
G 368
 
3.4%
J 347
 
3.2%
C 164
 
1.5%
S 148
 
1.4%
F 84
 
0.8%
A 78
 
0.7%
R 68
 
0.6%
M 66
 
0.6%
Other values (16) 392
 
3.6%
Decimal Number
ValueCountFrequency (%)
0 15213
29.8%
2 8980
17.6%
1 6847
13.4%
8 5316
 
10.4%
7 3074
 
6.0%
9 2836
 
5.6%
4 2740
 
5.4%
5 2301
 
4.5%
3 1938
 
3.8%
6 1854
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 28932
60.0%
. 14467
30.0%
: 4822
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 573
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 192989
65.9%
Common 99987
34.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 29255
15.2%
s 29167
15.1%
a 19997
10.4%
h 14537
 
7.5%
g 14264
 
7.4%
e 10188
 
5.3%
i 9990
 
5.2%
c 9869
 
5.1%
p 9392
 
4.9%
v 8724
 
4.5%
Other values (42) 37606
19.5%
Common
ValueCountFrequency (%)
/ 28932
28.9%
0 15213
15.2%
. 14467
14.5%
2 8980
 
9.0%
1 6847
 
6.8%
8 5316
 
5.3%
: 4822
 
4.8%
7 3074
 
3.1%
9 2836
 
2.8%
4 2740
 
2.7%
Other values (5) 6760
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292976
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 29255
 
10.0%
s 29167
 
10.0%
/ 28932
 
9.9%
a 19997
 
6.8%
0 15213
 
5.2%
h 14537
 
5.0%
. 14467
 
4.9%
g 14264
 
4.9%
e 10188
 
3.5%
i 9990
 
3.4%
Other values (57) 106966
36.5%

FrontCrashVideo
Text

MISSING 

Distinct2582
Distinct (%)61.7%
Missing10202
Missing (%)70.9%
Memory size112.5 KiB
2024-10-29T15:14:46.258500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length61
Mean length60.970356
Min length54

Characters and Unicode

Total characters255039
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1292 ?
Unique (%)30.9%

Sample

1st rowhttps://static.nhtsa.gov/crashTest/videos/2008/05Matrix-f.wmv
2nd rowhttps://static.nhtsa.gov/crashTest/videos/2008/06Prius-f.wmv
3rd rowhttps://static.nhtsa.gov/crashTest/videos/2008/06Rav4-f.wmv
4th rowhttps://static.nhtsa.gov/crashTest/videos/2008/05Sienna-f.wmv
5th rowhttps://static.nhtsa.gov/crashTest/videos/2008/06Tacoma4-f.wmv
ValueCountFrequency (%)
https://static.nhtsa.gov/crashtest/videos/2024/v10974c019.wmv 14
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2023/v10974c019.wmv 14
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2025/v10974c019.wmv 14
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2021/v10974c019.wmv 14
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2022/v10974c019.wmv 13
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2013/v07024c021.wmv 11
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2014/v07024c021.wmv 10
 
0.2%
https://static.nhtsa.gov/crashtest/videos/2021/v11288c019.mp4 8
 
0.2%
https://static.nhtsa.gov/crashtest/videos/2016/v08308c021.wmv 8
 
0.2%
https://static.nhtsa.gov/crashtest/videos/2020/v10974c019.wmv 7
 
0.2%
Other values (2572) 4071
97.3%
2024-10-29T15:14:46.457064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 25264
 
9.9%
s 25225
 
9.9%
/ 25098
 
9.8%
v 16104
 
6.3%
0 13734
 
5.4%
a 12909
 
5.1%
h 12577
 
4.9%
. 12549
 
4.9%
1 9149
 
3.6%
e 8625
 
3.4%
Other values (58) 93805
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 157196
61.6%
Decimal Number 47082
 
18.5%
Other Punctuation 41830
 
16.4%
Uppercase Letter 8457
 
3.3%
Dash Punctuation 463
 
0.2%
Connector Punctuation 9
 
< 0.1%
Control 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 25264
16.1%
s 25225
16.0%
v 16104
10.2%
a 12909
8.2%
h 12577
8.0%
e 8625
 
5.5%
o 8603
 
5.5%
i 8548
 
5.4%
c 8482
 
5.4%
r 4468
 
2.8%
Other values (16) 26391
16.8%
Uppercase Letter
ValueCountFrequency (%)
T 4236
50.1%
C 3703
43.8%
S 81
 
1.0%
A 47
 
0.6%
R 41
 
0.5%
F 40
 
0.5%
M 37
 
0.4%
X 36
 
0.4%
E 31
 
0.4%
L 24
 
0.3%
Other values (15) 181
 
2.1%
Decimal Number
ValueCountFrequency (%)
0 13734
29.2%
1 9149
19.4%
2 7931
16.8%
9 3517
 
7.5%
7 2946
 
6.3%
8 2209
 
4.7%
6 2155
 
4.6%
5 1992
 
4.2%
4 1930
 
4.1%
3 1519
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/ 25098
60.0%
. 12549
30.0%
: 4183
 
10.0%
Control
ValueCountFrequency (%)
1
50.0%
1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 463
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 165653
65.0%
Common 89386
35.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 25264
15.3%
s 25225
15.2%
v 16104
9.7%
a 12909
 
7.8%
h 12577
 
7.6%
e 8625
 
5.2%
o 8603
 
5.2%
i 8548
 
5.2%
c 8482
 
5.1%
r 4468
 
2.7%
Other values (41) 34848
21.0%
Common
ValueCountFrequency (%)
/ 25098
28.1%
0 13734
15.4%
. 12549
14.0%
1 9149
 
10.2%
2 7931
 
8.9%
: 4183
 
4.7%
9 3517
 
3.9%
7 2946
 
3.3%
8 2209
 
2.5%
6 2155
 
2.4%
Other values (7) 5915
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 255039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 25264
 
9.9%
s 25225
 
9.9%
/ 25098
 
9.8%
v 16104
 
6.3%
0 13734
 
5.4%
a 12909
 
5.1%
h 12577
 
4.9%
. 12549
 
4.9%
1 9149
 
3.6%
e 8625
 
3.4%
Other values (58) 93805
36.8%

OverallSideCrashRating
Categorical

IMBALANCE 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9234 
5
4886 
4
 
202
3
 
45
2
 
18

Length

Max length9
Median length9
Mean length6.1353493
Min length1

Characters and Unicode

Total characters88257
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9234
64.2%
5 4886
34.0%
4 202
 
1.4%
3 45
 
0.3%
2 18
 
0.1%

Length

2024-10-29T15:14:46.544691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:46.603203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9234
39.1%
rated 9234
39.1%
5 4886
20.7%
4 202
 
0.9%
3 45
 
0.2%
2 18
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t 18468
20.9%
N 9234
10.5%
o 9234
10.5%
9234
10.5%
R 9234
10.5%
a 9234
10.5%
e 9234
10.5%
d 9234
10.5%
5 4886
 
5.5%
4 202
 
0.2%
Other values (2) 63
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55404
62.8%
Uppercase Letter 18468
 
20.9%
Space Separator 9234
 
10.5%
Decimal Number 5151
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 18468
33.3%
o 9234
16.7%
a 9234
16.7%
e 9234
16.7%
d 9234
16.7%
Decimal Number
ValueCountFrequency (%)
5 4886
94.9%
4 202
 
3.9%
3 45
 
0.9%
2 18
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 9234
50.0%
R 9234
50.0%
Space Separator
ValueCountFrequency (%)
9234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73872
83.7%
Common 14385
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 18468
25.0%
N 9234
12.5%
o 9234
12.5%
R 9234
12.5%
a 9234
12.5%
e 9234
12.5%
d 9234
12.5%
Common
ValueCountFrequency (%)
9234
64.2%
5 4886
34.0%
4 202
 
1.4%
3 45
 
0.3%
2 18
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 18468
20.9%
N 9234
10.5%
o 9234
10.5%
9234
10.5%
R 9234
10.5%
a 9234
10.5%
e 9234
10.5%
d 9234
10.5%
5 4886
 
5.5%
4 202
 
0.2%
Other values (2) 63
 
0.1%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
7703 
5
5598 
4
 
607
3
 
386
1
 
58

Length

Max length9
Median length9
Mean length5.2839068
Min length1

Characters and Unicode

Total characters76009
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
Not Rated 7703
53.5%
5 5598
38.9%
4 607
 
4.2%
3 386
 
2.7%
1 58
 
0.4%
2 33
 
0.2%

Length

2024-10-29T15:14:46.667081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:46.728468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 7703
34.9%
rated 7703
34.9%
5 5598
25.3%
4 607
 
2.7%
3 386
 
1.7%
1 58
 
0.3%
2 33
 
0.1%

Most occurring characters

ValueCountFrequency (%)
t 15406
20.3%
N 7703
10.1%
o 7703
10.1%
7703
10.1%
R 7703
10.1%
a 7703
10.1%
e 7703
10.1%
d 7703
10.1%
5 5598
 
7.4%
4 607
 
0.8%
Other values (3) 477
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46218
60.8%
Uppercase Letter 15406
 
20.3%
Space Separator 7703
 
10.1%
Decimal Number 6682
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 15406
33.3%
o 7703
16.7%
a 7703
16.7%
e 7703
16.7%
d 7703
16.7%
Decimal Number
ValueCountFrequency (%)
5 5598
83.8%
4 607
 
9.1%
3 386
 
5.8%
1 58
 
0.9%
2 33
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 7703
50.0%
R 7703
50.0%
Space Separator
ValueCountFrequency (%)
7703
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 61624
81.1%
Common 14385
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 15406
25.0%
N 7703
12.5%
o 7703
12.5%
R 7703
12.5%
a 7703
12.5%
e 7703
12.5%
d 7703
12.5%
Common
ValueCountFrequency (%)
7703
53.5%
5 5598
38.9%
4 607
 
4.2%
3 386
 
2.7%
1 58
 
0.4%
2 33
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 15406
20.3%
N 7703
10.1%
o 7703
10.1%
7703
10.1%
R 7703
10.1%
a 7703
10.1%
e 7703
10.1%
d 7703
10.1%
5 5598
 
7.4%
4 607
 
0.8%
Other values (3) 477
 
0.6%

SideCrashPassengersideRating
Categorical

IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
8072 
5
5392 
4
 
497
3
 
320
2
 
76
Other values (2)
 
28

Length

Max length9
Median length9
Mean length5.4891206
Min length1

Characters and Unicode

Total characters78961
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
Not Rated 8072
56.1%
5 5392
37.5%
4 497
 
3.5%
3 320
 
2.2%
2 76
 
0.5%
1 17
 
0.1%
0 11
 
0.1%

Length

2024-10-29T15:14:46.794566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:46.856209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 8072
35.9%
rated 8072
35.9%
5 5392
24.0%
4 497
 
2.2%
3 320
 
1.4%
2 76
 
0.3%
1 17
 
0.1%
0 11
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 16144
20.4%
N 8072
10.2%
o 8072
10.2%
8072
10.2%
R 8072
10.2%
a 8072
10.2%
e 8072
10.2%
d 8072
10.2%
5 5392
 
6.8%
4 497
 
0.6%
Other values (4) 424
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 48432
61.3%
Uppercase Letter 16144
 
20.4%
Space Separator 8072
 
10.2%
Decimal Number 6313
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 5392
85.4%
4 497
 
7.9%
3 320
 
5.1%
2 76
 
1.2%
1 17
 
0.3%
0 11
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
t 16144
33.3%
o 8072
16.7%
a 8072
16.7%
e 8072
16.7%
d 8072
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 8072
50.0%
R 8072
50.0%
Space Separator
ValueCountFrequency (%)
8072
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 64576
81.8%
Common 14385
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 16144
25.0%
N 8072
12.5%
o 8072
12.5%
R 8072
12.5%
a 8072
12.5%
e 8072
12.5%
d 8072
12.5%
Common
ValueCountFrequency (%)
8072
56.1%
5 5392
37.5%
4 497
 
3.5%
3 320
 
2.2%
2 76
 
0.5%
1 17
 
0.1%
0 11
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78961
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 16144
20.4%
N 8072
10.2%
o 8072
10.2%
8072
10.2%
R 8072
10.2%
a 8072
10.2%
e 8072
10.2%
d 8072
10.2%
5 5392
 
6.8%
4 497
 
0.6%
Other values (4) 424
 
0.5%

SideCrashVideo
Text

MISSING 

Distinct2462
Distinct (%)60.9%
Missing10339
Missing (%)71.9%
Memory size112.5 KiB
2024-10-29T15:14:46.959942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length61
Mean length61.05561
Min length57

Characters and Unicode

Total characters247031
Distinct characters66
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1197 ?
Unique (%)29.6%

Sample

1st rowhttps://static.nhtsa.gov/crashTest/videos/2008/05Matrix-s.wmv
2nd rowhttps://static.nhtsa.gov/crashTest/videos/2008/07Prius-s .wmv
3rd rowhttps://static.nhtsa.gov/crashTest/videos/2008/07RAV4-s.wmv
4th rowhttps://static.nhtsa.gov/crashTest/videos/2008/06Sienna-s.wmv
5th rowhttps://static.nhtsa.gov/crashTest/videos/2008/06Tacoma4-s.mov
ValueCountFrequency (%)
https://static.nhtsa.gov/crashtest/videos/2016/v08310c013.wmv 13
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2023/v08997c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2022/v08997c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2024/v08997c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2025/v08997c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2021/v08997c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2013/v07003c013.wmv 11
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2014/v07003c013.wmv 10
 
0.2%
https://static.nhtsa.gov/crashtest/videos/2021/v11292c012.mp4 8
 
0.2%
https://static.nhtsa.gov/crashtest/videos/2025/v11127c012.wmv 7
 
0.2%
Other values (2453) 3941
97.3%
2024-10-29T15:14:47.161313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 24843
 
10.1%
t 24402
 
9.9%
/ 24276
 
9.8%
v 15650
 
6.3%
0 13159
 
5.3%
a 12440
 
5.0%
h 12164
 
4.9%
. 12138
 
4.9%
1 9075
 
3.7%
e 8310
 
3.4%
Other values (56) 90574
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 151668
61.4%
Decimal Number 46144
 
18.7%
Other Punctuation 40460
 
16.4%
Uppercase Letter 8277
 
3.4%
Dash Punctuation 444
 
0.2%
Connector Punctuation 34
 
< 0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 24843
16.4%
t 24402
16.1%
v 15650
10.3%
a 12440
8.2%
h 12164
8.0%
e 8310
 
5.5%
o 8278
 
5.5%
i 8253
 
5.4%
c 8184
 
5.4%
r 4264
 
2.8%
Other values (15) 24880
16.4%
Uppercase Letter
ValueCountFrequency (%)
T 4088
49.4%
C 3671
44.4%
S 94
 
1.1%
M 52
 
0.6%
A 45
 
0.5%
E 36
 
0.4%
F 32
 
0.4%
R 32
 
0.4%
X 32
 
0.4%
V 26
 
0.3%
Other values (15) 169
 
2.0%
Decimal Number
ValueCountFrequency (%)
0 13159
28.5%
1 9075
19.7%
2 7964
17.3%
3 3677
 
8.0%
9 2433
 
5.3%
4 2196
 
4.8%
8 2172
 
4.7%
7 2134
 
4.6%
5 1853
 
4.0%
6 1481
 
3.2%
Other Punctuation
ValueCountFrequency (%)
/ 24276
60.0%
. 12138
30.0%
: 4046
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 444
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 34
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 159945
64.7%
Common 87086
35.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 24843
15.5%
t 24402
15.3%
v 15650
9.8%
a 12440
 
7.8%
h 12164
 
7.6%
e 8310
 
5.2%
o 8278
 
5.2%
i 8253
 
5.2%
c 8184
 
5.1%
r 4264
 
2.7%
Other values (40) 33157
20.7%
Common
ValueCountFrequency (%)
/ 24276
27.9%
0 13159
15.1%
. 12138
13.9%
1 9075
 
10.4%
2 7964
 
9.1%
: 4046
 
4.6%
3 3677
 
4.2%
9 2433
 
2.8%
4 2196
 
2.5%
8 2172
 
2.5%
Other values (6) 5950
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 247031
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 24843
 
10.1%
t 24402
 
9.9%
/ 24276
 
9.8%
v 15650
 
6.3%
0 13159
 
5.3%
a 12440
 
5.0%
h 12164
 
4.9%
. 12138
 
4.9%
1 9075
 
3.7%
e 8310
 
3.4%
Other values (56) 90574
36.7%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9234 
5
4735 
4
 
313
3
 
73
2
 
28

Length

Max length9
Median length9
Mean length6.1353493
Min length1

Characters and Unicode

Total characters88257
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9234
64.2%
5 4735
32.9%
4 313
 
2.2%
3 73
 
0.5%
2 28
 
0.2%
1 2
 
< 0.1%

Length

2024-10-29T15:14:47.251067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:47.310282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9234
39.1%
rated 9234
39.1%
5 4735
20.0%
4 313
 
1.3%
3 73
 
0.3%
2 28
 
0.1%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 18468
20.9%
N 9234
10.5%
o 9234
10.5%
9234
10.5%
R 9234
10.5%
a 9234
10.5%
e 9234
10.5%
d 9234
10.5%
5 4735
 
5.4%
4 313
 
0.4%
Other values (3) 103
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55404
62.8%
Uppercase Letter 18468
 
20.9%
Space Separator 9234
 
10.5%
Decimal Number 5151
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 18468
33.3%
o 9234
16.7%
a 9234
16.7%
e 9234
16.7%
d 9234
16.7%
Decimal Number
ValueCountFrequency (%)
5 4735
91.9%
4 313
 
6.1%
3 73
 
1.4%
2 28
 
0.5%
1 2
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
N 9234
50.0%
R 9234
50.0%
Space Separator
ValueCountFrequency (%)
9234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73872
83.7%
Common 14385
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 18468
25.0%
N 9234
12.5%
o 9234
12.5%
R 9234
12.5%
a 9234
12.5%
e 9234
12.5%
d 9234
12.5%
Common
ValueCountFrequency (%)
9234
64.2%
5 4735
32.9%
4 313
 
2.2%
3 73
 
0.5%
2 28
 
0.2%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 18468
20.9%
N 9234
10.5%
o 9234
10.5%
9234
10.5%
R 9234
10.5%
a 9234
10.5%
e 9234
10.5%
d 9234
10.5%
5 4735
 
5.4%
4 313
 
0.4%
Other values (3) 103
 
0.1%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9424 
5
4683 
4
 
144
3
 
86
2
 
35
Other values (2)
 
13

Length

Max length9
Median length9
Mean length6.2410149
Min length1

Characters and Unicode

Total characters89777
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9424
65.5%
5 4683
32.6%
4 144
 
1.0%
3 86
 
0.6%
2 35
 
0.2%
0 11
 
0.1%
1 2
 
< 0.1%

Length

2024-10-29T15:14:47.375901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:47.547911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9424
39.6%
rated 9424
39.6%
5 4683
19.7%
4 144
 
0.6%
3 86
 
0.4%
2 35
 
0.1%
0 11
 
< 0.1%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 18848
21.0%
N 9424
10.5%
o 9424
10.5%
9424
10.5%
R 9424
10.5%
a 9424
10.5%
e 9424
10.5%
d 9424
10.5%
5 4683
 
5.2%
4 144
 
0.2%
Other values (4) 134
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 56544
63.0%
Uppercase Letter 18848
 
21.0%
Space Separator 9424
 
10.5%
Decimal Number 4961
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4683
94.4%
4 144
 
2.9%
3 86
 
1.7%
2 35
 
0.7%
0 11
 
0.2%
1 2
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
t 18848
33.3%
o 9424
16.7%
a 9424
16.7%
e 9424
16.7%
d 9424
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 9424
50.0%
R 9424
50.0%
Space Separator
ValueCountFrequency (%)
9424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 75392
84.0%
Common 14385
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 18848
25.0%
N 9424
12.5%
o 9424
12.5%
R 9424
12.5%
a 9424
12.5%
e 9424
12.5%
d 9424
12.5%
Common
ValueCountFrequency (%)
9424
65.5%
5 4683
32.6%
4 144
 
1.0%
3 86
 
0.6%
2 35
 
0.2%
0 11
 
0.1%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89777
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 18848
21.0%
N 9424
10.5%
o 9424
10.5%
9424
10.5%
R 9424
10.5%
a 9424
10.5%
e 9424
10.5%
d 9424
10.5%
5 4683
 
5.2%
4 144
 
0.2%
Other values (4) 134
 
0.1%

sideBarrierRating-Overall
Categorical

IMBALANCE 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9234 
5
4899 
4
 
199
3
 
46
2
 
7

Length

Max length9
Median length9
Mean length6.1353493
Min length1

Characters and Unicode

Total characters88257
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9234
64.2%
5 4899
34.1%
4 199
 
1.4%
3 46
 
0.3%
2 7
 
< 0.1%

Length

2024-10-29T15:14:47.615167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:47.673423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9234
39.1%
rated 9234
39.1%
5 4899
20.7%
4 199
 
0.8%
3 46
 
0.2%
2 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 18468
20.9%
N 9234
10.5%
o 9234
10.5%
9234
10.5%
R 9234
10.5%
a 9234
10.5%
e 9234
10.5%
d 9234
10.5%
5 4899
 
5.6%
4 199
 
0.2%
Other values (2) 53
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55404
62.8%
Uppercase Letter 18468
 
20.9%
Space Separator 9234
 
10.5%
Decimal Number 5151
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 18468
33.3%
o 9234
16.7%
a 9234
16.7%
e 9234
16.7%
d 9234
16.7%
Decimal Number
ValueCountFrequency (%)
5 4899
95.1%
4 199
 
3.9%
3 46
 
0.9%
2 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 9234
50.0%
R 9234
50.0%
Space Separator
ValueCountFrequency (%)
9234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73872
83.7%
Common 14385
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 18468
25.0%
N 9234
12.5%
o 9234
12.5%
R 9234
12.5%
a 9234
12.5%
e 9234
12.5%
d 9234
12.5%
Common
ValueCountFrequency (%)
9234
64.2%
5 4899
34.1%
4 199
 
1.4%
3 46
 
0.3%
2 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 18468
20.9%
N 9234
10.5%
o 9234
10.5%
9234
10.5%
R 9234
10.5%
a 9234
10.5%
e 9234
10.5%
d 9234
10.5%
5 4899
 
5.6%
4 199
 
0.2%
Other values (2) 53
 
0.1%

RolloverRating
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
7589 
4
4154 
5
1256 
3
1233 
2
 
101

Length

Max length9
Median length9
Mean length5.2205075
Min length1

Characters and Unicode

Total characters75097
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
Not Rated 7589
52.8%
4 4154
28.9%
5 1256
 
8.7%
3 1233
 
8.6%
2 101
 
0.7%
1 52
 
0.4%

Length

2024-10-29T15:14:47.742232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:47.805764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 7589
34.5%
rated 7589
34.5%
4 4154
18.9%
5 1256
 
5.7%
3 1233
 
5.6%
2 101
 
0.5%
1 52
 
0.2%

Most occurring characters

ValueCountFrequency (%)
t 15178
20.2%
N 7589
10.1%
o 7589
10.1%
7589
10.1%
R 7589
10.1%
a 7589
10.1%
e 7589
10.1%
d 7589
10.1%
4 4154
 
5.5%
5 1256
 
1.7%
Other values (3) 1386
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45534
60.6%
Uppercase Letter 15178
 
20.2%
Space Separator 7589
 
10.1%
Decimal Number 6796
 
9.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 15178
33.3%
o 7589
16.7%
a 7589
16.7%
e 7589
16.7%
d 7589
16.7%
Decimal Number
ValueCountFrequency (%)
4 4154
61.1%
5 1256
 
18.5%
3 1233
 
18.1%
2 101
 
1.5%
1 52
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
N 7589
50.0%
R 7589
50.0%
Space Separator
ValueCountFrequency (%)
7589
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60712
80.8%
Common 14385
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 15178
25.0%
N 7589
12.5%
o 7589
12.5%
R 7589
12.5%
a 7589
12.5%
e 7589
12.5%
d 7589
12.5%
Common
ValueCountFrequency (%)
7589
52.8%
4 4154
28.9%
5 1256
 
8.7%
3 1233
 
8.6%
2 101
 
0.7%
1 52
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75097
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 15178
20.2%
N 7589
10.1%
o 7589
10.1%
7589
10.1%
R 7589
10.1%
a 7589
10.1%
e 7589
10.1%
d 7589
10.1%
4 4154
 
5.5%
5 1256
 
1.7%
Other values (3) 1386
 
1.8%

RolloverRating2
Categorical

IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
13139 
4
 
704
3
 
336
5
 
146
2
 
51

Length

Max length9
Median length9
Mean length8.307056
Min length1

Characters and Unicode

Total characters119497
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
Not Rated 13139
91.3%
4 704
 
4.9%
3 336
 
2.3%
5 146
 
1.0%
2 51
 
0.4%
1 9
 
0.1%

Length

2024-10-29T15:14:47.877045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:47.935858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 13139
47.7%
rated 13139
47.7%
4 704
 
2.6%
3 336
 
1.2%
5 146
 
0.5%
2 51
 
0.2%
1 9
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 26278
22.0%
N 13139
11.0%
o 13139
11.0%
13139
11.0%
R 13139
11.0%
a 13139
11.0%
e 13139
11.0%
d 13139
11.0%
4 704
 
0.6%
3 336
 
0.3%
Other values (3) 206
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 78834
66.0%
Uppercase Letter 26278
 
22.0%
Space Separator 13139
 
11.0%
Decimal Number 1246
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 26278
33.3%
o 13139
16.7%
a 13139
16.7%
e 13139
16.7%
d 13139
16.7%
Decimal Number
ValueCountFrequency (%)
4 704
56.5%
3 336
27.0%
5 146
 
11.7%
2 51
 
4.1%
1 9
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
N 13139
50.0%
R 13139
50.0%
Space Separator
ValueCountFrequency (%)
13139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 105112
88.0%
Common 14385
 
12.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 26278
25.0%
N 13139
12.5%
o 13139
12.5%
R 13139
12.5%
a 13139
12.5%
e 13139
12.5%
d 13139
12.5%
Common
ValueCountFrequency (%)
13139
91.3%
4 704
 
4.9%
3 336
 
2.3%
5 146
 
1.0%
2 51
 
0.4%
1 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119497
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 26278
22.0%
N 13139
11.0%
o 13139
11.0%
13139
11.0%
R 13139
11.0%
a 13139
11.0%
e 13139
11.0%
d 13139
11.0%
4 704
 
0.6%
3 336
 
0.3%
Other values (3) 206
 
0.2%

RolloverPossibility
Real number (ℝ)

ZEROS 

Distinct128
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07400869
Minimum0
Maximum1.33
Zeros7860
Zeros (%)54.6%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:48.003488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.155
95-th percentile0.219
Maximum1.33
Range1.33
Interquartile range (IQR)0.155

Descriptive statistics

Standard deviation0.098295057
Coefficient of variation (CV)1.3281556
Kurtosis18.654617
Mean0.07400869
Median Absolute Deviation (MAD)0
Skewness2.5508706
Sum1064.615
Variance0.0096619182
MonotonicityNot monotonic
2024-10-29T15:14:48.079088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7860
54.6%
0.191 330
 
2.3%
0.198 313
 
2.2%
0.164 277
 
1.9%
0.169 256
 
1.8%
0.155 255
 
1.8%
0.179 254
 
1.8%
0.185 219
 
1.5%
0.095 218
 
1.5%
0.174 211
 
1.5%
Other values (118) 4192
29.1%
ValueCountFrequency (%)
0 7860
54.6%
0.052 5
 
< 0.1%
0.057 54
 
0.4%
0.066 14
 
0.1%
0.071 14
 
0.1%
0.079 11
 
0.1%
0.081 12
 
0.1%
0.082 13
 
0.1%
0.083 82
 
0.6%
0.084 1
 
< 0.1%
ValueCountFrequency (%)
1.33 3
 
< 0.1%
0.99 18
0.1%
0.924 9
0.1%
0.843 6
 
< 0.1%
0.516 6
 
< 0.1%
0.451 8
0.1%
0.423 5
 
< 0.1%
0.386 2
 
< 0.1%
0.376 17
0.1%
0.356 5
 
< 0.1%

RolloverPossibility2
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0090274592
Minimum0
Maximum0.306
Zeros13581
Zeros (%)94.4%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:48.151002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.101
Maximum0.306
Range0.306
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.039187564
Coefficient of variation (CV)4.3409296
Kurtosis20.708912
Mean0.0090274592
Median Absolute Deviation (MAD)0
Skewness4.55761
Sum129.86
Variance0.0015356652
MonotonicityNot monotonic
2024-10-29T15:14:48.225531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 13581
94.4%
0.191 76
 
0.5%
0.185 48
 
0.3%
0.212 38
 
0.3%
0.105 38
 
0.3%
0.101 32
 
0.2%
0.204 31
 
0.2%
0.198 30
 
0.2%
0.109 28
 
0.2%
0.237 27
 
0.2%
Other values (37) 456
 
3.2%
ValueCountFrequency (%)
0 13581
94.4%
0.082 8
 
0.1%
0.087 8
 
0.1%
0.09 9
 
0.1%
0.093 11
 
0.1%
0.095 10
 
0.1%
0.097 3
 
< 0.1%
0.099 10
 
0.1%
0.101 32
 
0.2%
0.103 18
 
0.1%
ValueCountFrequency (%)
0.306 3
 
< 0.1%
0.292 10
 
0.1%
0.279 21
0.1%
0.256 6
 
< 0.1%
0.246 21
0.1%
0.237 27
0.2%
0.228 16
0.1%
0.219 15
 
0.1%
0.212 38
0.3%
0.209 2
 
< 0.1%

dynamicTipResult
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
7890 
No Tip
6492 
No TIP
 
3

Length

Max length6
Median length1
Mean length3.25756
Min length1

Characters and Unicode

Total characters46860
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd rowNo Tip
4th rowNo Tip
5th rowNo Tip

Common Values

ValueCountFrequency (%)
7890
54.8%
No Tip 6492
45.1%
No TIP 3
 
< 0.1%

Length

2024-10-29T15:14:48.295478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:48.347443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
no 6495
50.0%
tip 6495
50.0%

Most occurring characters

ValueCountFrequency (%)
14385
30.7%
N 6495
13.9%
o 6495
13.9%
T 6495
13.9%
i 6492
13.9%
p 6492
13.9%
I 3
 
< 0.1%
P 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19479
41.6%
Space Separator 14385
30.7%
Uppercase Letter 12996
27.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 6495
50.0%
T 6495
50.0%
I 3
 
< 0.1%
P 3
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
o 6495
33.3%
i 6492
33.3%
p 6492
33.3%
Space Separator
ValueCountFrequency (%)
14385
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32475
69.3%
Common 14385
30.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 6495
20.0%
o 6495
20.0%
T 6495
20.0%
i 6492
20.0%
p 6492
20.0%
I 3
 
< 0.1%
P 3
 
< 0.1%
Common
ValueCountFrequency (%)
14385
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14385
30.7%
N 6495
13.9%
o 6495
13.9%
T 6495
13.9%
i 6492
13.9%
p 6492
13.9%
I 3
 
< 0.1%
P 3
 
< 0.1%

SidePoleCrashRating
Categorical

IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Not Rated
9201 
5
4604 
4
 
401
3
 
84
2
 
57

Length

Max length9
Median length9
Mean length6.1169969
Min length1

Characters and Unicode

Total characters87993
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Rated
2nd rowNot Rated
3rd rowNot Rated
4th rowNot Rated
5th rowNot Rated

Common Values

ValueCountFrequency (%)
Not Rated 9201
64.0%
5 4604
32.0%
4 401
 
2.8%
3 84
 
0.6%
2 57
 
0.4%
1 38
 
0.3%

Length

2024-10-29T15:14:48.412866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:48.474941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 9201
39.0%
rated 9201
39.0%
5 4604
19.5%
4 401
 
1.7%
3 84
 
0.4%
2 57
 
0.2%
1 38
 
0.2%

Most occurring characters

ValueCountFrequency (%)
t 18402
20.9%
N 9201
10.5%
o 9201
10.5%
9201
10.5%
R 9201
10.5%
a 9201
10.5%
e 9201
10.5%
d 9201
10.5%
5 4604
 
5.2%
4 401
 
0.5%
Other values (3) 179
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55206
62.7%
Uppercase Letter 18402
 
20.9%
Space Separator 9201
 
10.5%
Decimal Number 5184
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 18402
33.3%
o 9201
16.7%
a 9201
16.7%
e 9201
16.7%
d 9201
16.7%
Decimal Number
ValueCountFrequency (%)
5 4604
88.8%
4 401
 
7.7%
3 84
 
1.6%
2 57
 
1.1%
1 38
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
N 9201
50.0%
R 9201
50.0%
Space Separator
ValueCountFrequency (%)
9201
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73608
83.7%
Common 14385
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 18402
25.0%
N 9201
12.5%
o 9201
12.5%
R 9201
12.5%
a 9201
12.5%
e 9201
12.5%
d 9201
12.5%
Common
ValueCountFrequency (%)
9201
64.0%
5 4604
32.0%
4 401
 
2.8%
3 84
 
0.6%
2 57
 
0.4%
1 38
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87993
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 18402
20.9%
N 9201
10.5%
o 9201
10.5%
9201
10.5%
R 9201
10.5%
a 9201
10.5%
e 9201
10.5%
d 9201
10.5%
5 4604
 
5.2%
4 401
 
0.5%
Other values (3) 179
 
0.2%

NHTSAElectronicStabilityControl
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
Standard
12009 
No
2086 
Optional
 
290

Length

Max length8
Median length8
Mean length7.129927
Min length2

Characters and Unicode

Total characters102564
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOptional
2nd rowOptional
3rd rowStandard
4th rowStandard
5th rowOptional

Common Values

ValueCountFrequency (%)
Standard 12009
83.5%
No 2086
 
14.5%
Optional 290
 
2.0%

Length

2024-10-29T15:14:48.544171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:48.599684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
standard 12009
83.5%
no 2086
 
14.5%
optional 290
 
2.0%

Most occurring characters

ValueCountFrequency (%)
a 24308
23.7%
d 24018
23.4%
t 12299
12.0%
n 12299
12.0%
S 12009
11.7%
r 12009
11.7%
o 2376
 
2.3%
N 2086
 
2.0%
O 290
 
0.3%
p 290
 
0.3%
Other values (2) 580
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 88179
86.0%
Uppercase Letter 14385
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 24308
27.6%
d 24018
27.2%
t 12299
13.9%
n 12299
13.9%
r 12009
13.6%
o 2376
 
2.7%
p 290
 
0.3%
i 290
 
0.3%
l 290
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
S 12009
83.5%
N 2086
 
14.5%
O 290
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 102564
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 24308
23.7%
d 24018
23.4%
t 12299
12.0%
n 12299
12.0%
S 12009
11.7%
r 12009
11.7%
o 2376
 
2.3%
N 2086
 
2.0%
O 290
 
0.3%
p 290
 
0.3%
Other values (2) 580
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102564
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 24308
23.7%
d 24018
23.4%
t 12299
12.0%
n 12299
12.0%
S 12009
11.7%
r 12009
11.7%
o 2376
 
2.3%
N 2086
 
2.0%
O 290
 
0.3%
p 290
 
0.3%
Other values (2) 580
 
0.6%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
No
7543 
Standard
3368 
Optional
2980 
Standard & Optional
 
445
Not Available
 
49

Length

Max length19
Median length2
Mean length5.2111227
Min length2

Characters and Unicode

Total characters74962
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 7543
52.4%
Standard 3368
23.4%
Optional 2980
 
20.7%
Standard & Optional 445
 
3.1%
Not Available 49
 
0.3%

Length

2024-10-29T15:14:48.663688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:48.727034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
no 7543
49.2%
standard 3813
24.9%
optional 3425
22.4%
445
 
2.9%
not 49
 
0.3%
available 49
 
0.3%

Most occurring characters

ValueCountFrequency (%)
a 11149
14.9%
o 11017
14.7%
d 7626
10.2%
N 7592
10.1%
t 7287
9.7%
n 7238
9.7%
S 3813
 
5.1%
r 3813
 
5.1%
l 3523
 
4.7%
i 3474
 
4.6%
Other values (8) 8430
11.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 58699
78.3%
Uppercase Letter 14879
 
19.8%
Space Separator 939
 
1.3%
Other Punctuation 445
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 11149
19.0%
o 11017
18.8%
d 7626
13.0%
t 7287
12.4%
n 7238
12.3%
r 3813
 
6.5%
l 3523
 
6.0%
i 3474
 
5.9%
p 3425
 
5.8%
v 49
 
0.1%
Other values (2) 98
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 7592
51.0%
S 3813
25.6%
O 3425
23.0%
A 49
 
0.3%
Space Separator
ValueCountFrequency (%)
939
100.0%
Other Punctuation
ValueCountFrequency (%)
& 445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73578
98.2%
Common 1384
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 11149
15.2%
o 11017
15.0%
d 7626
10.4%
N 7592
10.3%
t 7287
9.9%
n 7238
9.8%
S 3813
 
5.2%
r 3813
 
5.2%
l 3523
 
4.8%
i 3474
 
4.7%
Other values (6) 7046
9.6%
Common
ValueCountFrequency (%)
939
67.8%
& 445
32.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 11149
14.9%
o 11017
14.7%
d 7626
10.2%
N 7592
10.1%
t 7287
9.7%
n 7238
9.7%
S 3813
 
5.1%
r 3813
 
5.1%
l 3523
 
4.7%
i 3474
 
4.6%
Other values (8) 8430
11.2%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
No
8212 
Optional
3023 
Standard
2848 
Not Available
 
155
Standard & Optional
 
147

Length

Max length19
Median length2
Mean length4.7410497
Min length2

Characters and Unicode

Total characters68200
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 8212
57.1%
Optional 3023
 
21.0%
Standard 2848
 
19.8%
Not Available 155
 
1.1%
Standard & Optional 147
 
1.0%

Length

2024-10-29T15:14:48.797436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:14:48.854573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
no 8212
55.4%
optional 3170
 
21.4%
standard 2995
 
20.2%
not 155
 
1.0%
available 155
 
1.0%
147
 
1.0%

Most occurring characters

ValueCountFrequency (%)
o 11537
16.9%
a 9470
13.9%
N 8367
12.3%
t 6320
9.3%
n 6165
9.0%
d 5990
8.8%
l 3480
 
5.1%
i 3325
 
4.9%
O 3170
 
4.6%
p 3170
 
4.6%
Other values (8) 7206
10.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52917
77.6%
Uppercase Letter 14687
 
21.5%
Space Separator 449
 
0.7%
Other Punctuation 147
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 11537
21.8%
a 9470
17.9%
t 6320
11.9%
n 6165
11.7%
d 5990
11.3%
l 3480
 
6.6%
i 3325
 
6.3%
p 3170
 
6.0%
r 2995
 
5.7%
v 155
 
0.3%
Other values (2) 310
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
N 8367
57.0%
O 3170
 
21.6%
S 2995
 
20.4%
A 155
 
1.1%
Space Separator
ValueCountFrequency (%)
449
100.0%
Other Punctuation
ValueCountFrequency (%)
& 147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67604
99.1%
Common 596
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 11537
17.1%
a 9470
14.0%
N 8367
12.4%
t 6320
9.3%
n 6165
9.1%
d 5990
8.9%
l 3480
 
5.1%
i 3325
 
4.9%
O 3170
 
4.7%
p 3170
 
4.7%
Other values (6) 6610
9.8%
Common
ValueCountFrequency (%)
449
75.3%
& 147
 
24.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 11537
16.9%
a 9470
13.9%
N 8367
12.3%
t 6320
9.3%
n 6165
9.0%
d 5990
8.8%
l 3480
 
5.1%
i 3325
 
4.9%
O 3170
 
4.6%
p 3170
 
4.6%
Other values (8) 7206
10.6%

ComplaintsCount
Real number (ℝ)

ZEROS 

Distinct908
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.66945
Minimum0
Maximum5054
Zeros2645
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:48.924914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median25
Q3130
95-th percentile647
Maximum5054
Range5054
Interquartile range (IQR)128

Descriptive statistics

Standard deviation295.53772
Coefficient of variation (CV)2.1783661
Kurtosis33.856866
Mean135.66945
Median Absolute Deviation (MAD)25
Skewness4.7404191
Sum1951605
Variance87342.543
MonotonicityNot monotonic
2024-10-29T15:14:49.001036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2645
 
18.4%
1 650
 
4.5%
2 474
 
3.3%
3 334
 
2.3%
5 299
 
2.1%
4 273
 
1.9%
6 229
 
1.6%
7 198
 
1.4%
9 193
 
1.3%
8 166
 
1.2%
Other values (898) 8924
62.0%
ValueCountFrequency (%)
0 2645
18.4%
1 650
 
4.5%
2 474
 
3.3%
3 334
 
2.3%
4 273
 
1.9%
5 299
 
2.1%
6 229
 
1.6%
7 198
 
1.4%
8 166
 
1.2%
9 193
 
1.3%
ValueCountFrequency (%)
5054 1
 
< 0.1%
3881 2
 
< 0.1%
3777 1
 
< 0.1%
3714 2
 
< 0.1%
3618 3
< 0.1%
2991 1
 
< 0.1%
2762 1
 
< 0.1%
2756 1
 
< 0.1%
2606 2
 
< 0.1%
2584 6
< 0.1%

RecallsCount
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7936044
Minimum0
Maximum41
Zeros3154
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:49.068617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile13
Maximum41
Range41
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.4205397
Coefficient of variation (CV)1.1652611
Kurtosis8.7958917
Mean3.7936044
Median Absolute Deviation (MAD)2
Skewness2.327058
Sum54571
Variance19.541172
MonotonicityNot monotonic
2024-10-29T15:14:49.132799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 3154
21.9%
1 2188
15.2%
2 1873
13.0%
3 1564
10.9%
4 1211
 
8.4%
5 977
 
6.8%
6 791
 
5.5%
7 594
 
4.1%
9 331
 
2.3%
8 321
 
2.2%
Other values (24) 1381
9.6%
ValueCountFrequency (%)
0 3154
21.9%
1 2188
15.2%
2 1873
13.0%
3 1564
10.9%
4 1211
 
8.4%
5 977
 
6.8%
6 791
 
5.5%
7 594
 
4.1%
8 321
 
2.2%
9 331
 
2.3%
ValueCountFrequency (%)
41 7
< 0.1%
40 2
 
< 0.1%
37 2
 
< 0.1%
36 11
0.1%
34 2
 
< 0.1%
33 2
 
< 0.1%
29 2
 
< 0.1%
27 4
 
< 0.1%
26 12
0.1%
24 16
0.1%

InvestigationCount
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.96232186
Minimum0
Maximum26
Zeros8395
Zeros (%)58.4%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:49.192781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum26
Range26
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9030225
Coefficient of variation (CV)1.9775322
Kurtosis20.156127
Mean0.96232186
Median Absolute Deviation (MAD)0
Skewness3.8628727
Sum13843
Variance3.6214946
MonotonicityNot monotonic
2024-10-29T15:14:49.255007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 8395
58.4%
1 3157
 
21.9%
2 1258
 
8.7%
3 676
 
4.7%
4 265
 
1.8%
5 163
 
1.1%
6 108
 
0.8%
7 84
 
0.6%
9 63
 
0.4%
8 55
 
0.4%
Other values (10) 161
 
1.1%
ValueCountFrequency (%)
0 8395
58.4%
1 3157
 
21.9%
2 1258
 
8.7%
3 676
 
4.7%
4 265
 
1.8%
5 163
 
1.1%
6 108
 
0.8%
7 84
 
0.6%
8 55
 
0.4%
9 63
 
0.4%
ValueCountFrequency (%)
26 1
 
< 0.1%
20 1
 
< 0.1%
18 2
 
< 0.1%
16 2
 
< 0.1%
15 7
 
< 0.1%
14 44
0.3%
13 36
0.3%
12 9
 
0.1%
11 23
0.2%
10 36
0.3%

ModelYear
Real number (ℝ)

Distinct33
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.7366
Minimum1990
Maximum2025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:49.316319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1990
5-th percentile1996
Q12012
median2017
Q32021
95-th percentile2024
Maximum2025
Range35
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.4248501
Coefficient of variation (CV)0.0041816137
Kurtosis0.57040378
Mean2014.7366
Median Absolute Deviation (MAD)5
Skewness-1.1167875
Sum28981986
Variance70.978099
MonotonicityNot monotonic
2024-10-29T15:14:49.388436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2022 879
 
6.1%
2023 872
 
6.1%
2019 850
 
5.9%
2024 840
 
5.8%
2021 822
 
5.7%
2020 812
 
5.6%
2018 797
 
5.5%
2015 790
 
5.5%
2017 787
 
5.5%
2016 747
 
5.2%
Other values (23) 6189
43.0%
ValueCountFrequency (%)
1990 65
0.5%
1991 101
0.7%
1992 107
0.7%
1993 144
1.0%
1994 119
0.8%
1995 128
0.9%
1996 144
1.0%
1997 153
1.1%
1998 108
0.8%
1999 114
0.8%
ValueCountFrequency (%)
2025 666
4.6%
2024 840
5.8%
2023 872
6.1%
2022 879
6.1%
2021 822
5.7%
2020 812
5.6%
2019 850
5.9%
2018 797
5.5%
2017 787
5.5%
2016 747
5.2%

Make
Text

Distinct64
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:49.479557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6.1810219
Min length2

Characters and Unicode

Total characters88914
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowTOYOTA
2nd rowTOYOTA
3rd rowTOYOTA
4th rowTOYOTA
5th rowTOYOTA
ValueCountFrequency (%)
ford 1162
 
8.0%
chevrolet 1116
 
7.7%
bmw 831
 
5.7%
toyota 816
 
5.6%
porsche 786
 
5.4%
mercedes-benz 710
 
4.9%
gmc 690
 
4.7%
nissan 650
 
4.5%
audi 623
 
4.3%
lexus 518
 
3.6%
Other values (55) 6645
45.7%
2024-10-29T15:14:49.680620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 9133
 
10.3%
O 7394
 
8.3%
A 6631
 
7.5%
R 5853
 
6.6%
I 5467
 
6.1%
S 5155
 
5.8%
C 5093
 
5.7%
N 4949
 
5.6%
D 4860
 
5.5%
L 4567
 
5.1%
Other values (17) 29812
33.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 87944
98.9%
Dash Punctuation 808
 
0.9%
Space Separator 162
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 9133
 
10.4%
O 7394
 
8.4%
A 6631
 
7.5%
R 5853
 
6.7%
I 5467
 
6.2%
S 5155
 
5.9%
C 5093
 
5.8%
N 4949
 
5.6%
D 4860
 
5.5%
L 4567
 
5.2%
Other values (15) 28842
32.8%
Dash Punctuation
ValueCountFrequency (%)
- 808
100.0%
Space Separator
ValueCountFrequency (%)
162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 87944
98.9%
Common 970
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 9133
 
10.4%
O 7394
 
8.4%
A 6631
 
7.5%
R 5853
 
6.7%
I 5467
 
6.2%
S 5155
 
5.9%
C 5093
 
5.8%
N 4949
 
5.6%
D 4860
 
5.5%
L 4567
 
5.2%
Other values (15) 28842
32.8%
Common
ValueCountFrequency (%)
- 808
83.3%
162
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88914
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 9133
 
10.3%
O 7394
 
8.3%
A 6631
 
7.5%
R 5853
 
6.6%
I 5467
 
6.1%
S 5155
 
5.8%
C 5093
 
5.7%
N 4949
 
5.6%
D 4860
 
5.5%
L 4567
 
5.1%
Other values (17) 29812
33.5%

Model
Text

Distinct2281
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:49.887894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length9.3676051
Min length1

Characters and Unicode

Total characters134753
Distinct characters65
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique523 ?
Unique (%)3.6%

Sample

1st rowMATRIX
2nd rowPRIUS
3rd rowRAV4
4th rowSIENNA
5th rowTACOMA
ValueCountFrequency (%)
2500 480
 
2.0%
1500 422
 
1.7%
hybrid 404
 
1.7%
cab 314
 
1.3%
s 304
 
1.2%
sierra 283
 
1.2%
silverado 276
 
1.1%
911 275
 
1.1%
series 262
 
1.1%
crew 245
 
1.0%
Other values (1225) 21114
86.6%
2024-10-29T15:14:50.117501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 11844
 
8.8%
R 11499
 
8.5%
E 10999
 
8.2%
10017
 
7.4%
S 8641
 
6.4%
I 6335
 
4.7%
T 6280
 
4.7%
C 6257
 
4.6%
O 6237
 
4.6%
N 5963
 
4.4%
Other values (55) 50681
37.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 107367
79.7%
Decimal Number 14878
 
11.0%
Space Separator 10017
 
7.4%
Dash Punctuation 1540
 
1.1%
Close Punctuation 299
 
0.2%
Open Punctuation 299
 
0.2%
Other Punctuation 228
 
0.2%
Lowercase Letter 118
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 11844
11.0%
R 11499
10.7%
E 10999
 
10.2%
S 8641
 
8.0%
I 6335
 
5.9%
T 6280
 
5.8%
C 6257
 
5.8%
O 6237
 
5.8%
N 5963
 
5.6%
L 4734
 
4.4%
Other values (17) 28578
26.6%
Lowercase Letter
ValueCountFrequency (%)
e 19
16.1%
a 14
11.9%
s 14
11.9%
r 14
11.9%
n 10
8.5%
g 8
6.8%
t 8
6.8%
i 7
 
5.9%
l 6
 
5.1%
o 3
 
2.5%
Other values (8) 15
12.7%
Decimal Number
ValueCountFrequency (%)
0 4708
31.6%
5 2911
19.6%
1 1644
 
11.0%
3 1326
 
8.9%
2 1150
 
7.7%
4 918
 
6.2%
6 649
 
4.4%
8 568
 
3.8%
9 552
 
3.7%
7 452
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 82
36.0%
. 68
29.8%
/ 57
25.0%
& 19
 
8.3%
" 2
 
0.9%
Space Separator
ValueCountFrequency (%)
10017
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1540
100.0%
Close Punctuation
ValueCountFrequency (%)
) 299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 299
100.0%
Math Symbol
ValueCountFrequency (%)
+ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 107485
79.8%
Common 27268
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 11844
11.0%
R 11499
10.7%
E 10999
 
10.2%
S 8641
 
8.0%
I 6335
 
5.9%
T 6280
 
5.8%
C 6257
 
5.8%
O 6237
 
5.8%
N 5963
 
5.5%
L 4734
 
4.4%
Other values (35) 28696
26.7%
Common
ValueCountFrequency (%)
10017
36.7%
0 4708
17.3%
5 2911
 
10.7%
1 1644
 
6.0%
- 1540
 
5.6%
3 1326
 
4.9%
2 1150
 
4.2%
4 918
 
3.4%
6 649
 
2.4%
8 568
 
2.1%
Other values (10) 1837
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134740
> 99.9%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 11844
 
8.8%
R 11499
 
8.5%
E 10999
 
8.2%
10017
 
7.4%
S 8641
 
6.4%
I 6335
 
4.7%
T 6280
 
4.7%
C 6257
 
4.6%
O 6237
 
4.6%
N 5963
 
4.4%
Other values (54) 50668
37.6%
None
ValueCountFrequency (%)
É 13
100.0%
Distinct14379
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:50.277713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length55
Mean length30.580327
Min length13

Characters and Unicode

Total characters439898
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14373 ?
Unique (%)99.9%

Sample

1st row2008 Toyota Matrix 4-DR. w/SAB
2nd row2008 Toyota Prius 4-DR.w/SAB
3rd row2008 Toyota RAV4 4-DR. w/SAB
4th row2008 Toyota Sienna w/SAB
5th row2008 Toyota Tacoma 4-DR.
ValueCountFrequency (%)
awd 3900
 
4.6%
suv 3636
 
4.2%
dr 3563
 
4.2%
4 2787
 
3.3%
rwd 2729
 
3.2%
fwd 2550
 
3.0%
4-dr 1904
 
2.2%
w/sab 1392
 
1.6%
4wd 1258
 
1.5%
ford 1162
 
1.4%
Other values (1419) 60801
71.0%
2024-10-29T15:14:50.522685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71408
 
16.2%
2 23302
 
5.3%
0 21284
 
4.8%
e 19811
 
4.5%
D 18097
 
4.1%
a 17235
 
3.9%
r 15561
 
3.5%
o 13421
 
3.1%
W 12464
 
2.8%
R 11995
 
2.7%
Other values (66) 215320
48.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 154929
35.2%
Uppercase Letter 120724
27.4%
Decimal Number 82060
18.7%
Space Separator 71408
16.2%
Other Punctuation 5151
 
1.2%
Dash Punctuation 4874
 
1.1%
Close Punctuation 372
 
0.1%
Open Punctuation 372
 
0.1%
Math Symbol 7
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 19811
12.8%
a 17235
11.1%
r 15561
10.0%
o 13421
 
8.7%
i 10688
 
6.9%
n 10279
 
6.6%
s 9185
 
5.9%
l 7694
 
5.0%
t 7388
 
4.8%
d 7237
 
4.7%
Other values (17) 36430
23.5%
Uppercase Letter
ValueCountFrequency (%)
D 18097
15.0%
W 12464
10.3%
R 11995
9.9%
S 10340
 
8.6%
C 10147
 
8.4%
A 8318
 
6.9%
V 6164
 
5.1%
U 5168
 
4.3%
B 4764
 
3.9%
F 4755
 
3.9%
Other values (16) 28512
23.6%
Decimal Number
ValueCountFrequency (%)
2 23302
28.4%
0 21284
25.9%
1 10549
12.9%
4 9081
 
11.1%
5 5210
 
6.3%
9 4331
 
5.3%
3 3536
 
4.3%
8 1819
 
2.2%
6 1544
 
1.9%
7 1404
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 2856
55.4%
. 2188
42.5%
, 82
 
1.6%
& 20
 
0.4%
" 2
 
< 0.1%
' 2
 
< 0.1%
# 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
71408
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4874
100.0%
Close Punctuation
ValueCountFrequency (%)
) 372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 372
100.0%
Math Symbol
ValueCountFrequency (%)
+ 7
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 275653
62.7%
Common 164245
37.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 19811
 
7.2%
D 18097
 
6.6%
a 17235
 
6.3%
r 15561
 
5.6%
o 13421
 
4.9%
W 12464
 
4.5%
R 11995
 
4.4%
i 10688
 
3.9%
S 10340
 
3.8%
n 10279
 
3.7%
Other values (43) 135762
49.3%
Common
ValueCountFrequency (%)
71408
43.5%
2 23302
 
14.2%
0 21284
 
13.0%
1 10549
 
6.4%
4 9081
 
5.5%
5 5210
 
3.2%
- 4874
 
3.0%
9 4331
 
2.6%
3 3536
 
2.2%
/ 2856
 
1.7%
Other values (13) 7814
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 439885
> 99.9%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71408
 
16.2%
2 23302
 
5.3%
0 21284
 
4.8%
e 19811
 
4.5%
D 18097
 
4.1%
a 17235
 
3.9%
r 15561
 
3.5%
o 13421
 
3.1%
W 12464
 
2.8%
R 11995
 
2.7%
Other values (65) 215307
48.9%
None
ValueCountFrequency (%)
é 13
100.0%

VehicleId
Real number (ℝ)

UNIQUE 

Distinct14385
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11167.708
Minimum2500
Maximum20776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.5 KiB
2024-10-29T15:14:50.614782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile3221.2
Q16229
median11135
Q315637
95-th percentile19979.8
Maximum20776
Range18276
Interquartile range (IQR)9408

Descriptive statistics

Standard deviation5398.8052
Coefficient of variation (CV)0.48343002
Kurtosis-1.2041631
Mean11167.708
Median Absolute Deviation (MAD)4700
Skewness0.1016747
Sum1.6064748 × 108
Variance29147098
MonotonicityStrictly increasing
2024-10-29T15:14:50.689244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2500 1
 
< 0.1%
14329 1
 
< 0.1%
14246 1
 
< 0.1%
14247 1
 
< 0.1%
14248 1
 
< 0.1%
14249 1
 
< 0.1%
14250 1
 
< 0.1%
14251 1
 
< 0.1%
14252 1
 
< 0.1%
14253 1
 
< 0.1%
Other values (14375) 14375
99.9%
ValueCountFrequency (%)
2500 1
< 0.1%
2501 1
< 0.1%
2502 1
< 0.1%
2503 1
< 0.1%
2504 1
< 0.1%
2505 1
< 0.1%
2506 1
< 0.1%
2507 1
< 0.1%
2508 1
< 0.1%
2509 1
< 0.1%
ValueCountFrequency (%)
20776 1
< 0.1%
20775 1
< 0.1%
20774 1
< 0.1%
20773 1
< 0.1%
20772 1
< 0.1%
20771 1
< 0.1%
20770 1
< 0.1%
20769 1
< 0.1%
20768 1
< 0.1%
20767 1
< 0.1%

SideCrashPicture
Text

MISSING 

Distinct2978
Distinct (%)64.3%
Missing9757
Missing (%)67.8%
Memory size112.5 KiB
2024-10-29T15:14:50.796312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length61
Mean length60.883751
Min length55

Characters and Unicode

Total characters281770
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1669 ?
Unique (%)36.1%

Sample

1st rowhttps://static.nhtsa.gov/crashTest/images/2008/07Prius-s.jpg
2nd rowhttps://static.nhtsa.gov/crashTest/images/2008/07RAV4-s.jpg
3rd rowhttps://static.nhtsa.gov/crashTest/images/2008/06Sienna-s.jpg
4th rowhttps://static.nhtsa.gov/crashTest/images/2008/06Tacoma4-s.JPG
5th rowhttps://static.nhtsa.gov/crashTest/images/2008/05Tacoma-s.jpg
ValueCountFrequency (%)
https://static.nhtsa.gov/crashtest/images/2016/v08310p106.jpg 13
 
0.3%
https://static.nhtsa.gov/crashtest/images/2024/v08997p105.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2022/v08997p105.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2023/v08997p105.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2025/v08997p105.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2021/v08997p105.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2013/v07003p057.jpg 11
 
0.2%
https://static.nhtsa.gov/crashtest/images/2014/v07003p057.jpg 10
 
0.2%
https://static.nhtsa.gov/crashtest/images/2021/v11292p148.jpg 8
 
0.2%
https://static.nhtsa.gov/crashtest/images/2023/v11127p105.jpg 7
 
0.2%
Other values (2968) 4519
97.6%
2024-10-29T15:14:51.093522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 28854
 
10.2%
t 28032
 
9.9%
/ 27768
 
9.9%
a 19117
 
6.8%
0 14017
 
5.0%
h 13929
 
4.9%
. 13883
 
4.9%
g 13495
 
4.8%
e 9636
 
3.4%
i 9541
 
3.4%
Other values (57) 103498
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 173954
61.7%
Decimal Number 49753
 
17.7%
Other Punctuation 46279
 
16.4%
Uppercase Letter 10838
 
3.8%
Dash Punctuation 730
 
0.3%
Connector Punctuation 216
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 28854
16.6%
t 28032
16.1%
a 19117
11.0%
h 13929
8.0%
g 13495
7.8%
e 9636
 
5.5%
i 9541
 
5.5%
c 9459
 
5.4%
p 8833
 
5.1%
v 8436
 
4.8%
Other values (16) 24622
14.2%
Uppercase Letter
ValueCountFrequency (%)
T 4705
43.4%
P 4243
39.1%
G 519
 
4.8%
J 499
 
4.6%
S 163
 
1.5%
C 119
 
1.1%
M 76
 
0.7%
A 73
 
0.7%
E 51
 
0.5%
R 50
 
0.5%
Other values (16) 340
 
3.1%
Decimal Number
ValueCountFrequency (%)
0 14017
28.2%
1 9472
19.0%
2 8036
16.2%
5 3338
 
6.7%
4 2970
 
6.0%
9 2913
 
5.9%
7 2452
 
4.9%
8 2400
 
4.8%
3 2141
 
4.3%
6 2014
 
4.0%
Other Punctuation
ValueCountFrequency (%)
/ 27768
60.0%
. 13883
30.0%
: 4628
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 730
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 184792
65.6%
Common 96978
34.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 28854
15.6%
t 28032
15.2%
a 19117
10.3%
h 13929
 
7.5%
g 13495
 
7.3%
e 9636
 
5.2%
i 9541
 
5.2%
c 9459
 
5.1%
p 8833
 
4.8%
v 8436
 
4.6%
Other values (42) 35460
19.2%
Common
ValueCountFrequency (%)
/ 27768
28.6%
0 14017
14.5%
. 13883
14.3%
1 9472
 
9.8%
2 8036
 
8.3%
: 4628
 
4.8%
5 3338
 
3.4%
4 2970
 
3.1%
9 2913
 
3.0%
7 2452
 
2.5%
Other values (5) 7501
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 281770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 28854
 
10.2%
t 28032
 
9.9%
/ 27768
 
9.9%
a 19117
 
6.8%
0 14017
 
5.0%
h 13929
 
4.9%
. 13883
 
4.9%
g 13495
 
4.8%
e 9636
 
3.4%
i 9541
 
3.4%
Other values (57) 103498
36.7%

SidePolePicture
Text

MISSING 

Distinct2071
Distinct (%)55.3%
Missing10642
Missing (%)74.0%
Memory size112.5 KiB
2024-10-29T15:14:51.213327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length61
Mean length61
Min length61

Characters and Unicode

Total characters228323
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique756 ?
Unique (%)20.2%

Sample

1st rowhttps://static.nhtsa.gov/crashTest/images/2012/v07859P071.jpg
2nd rowhttps://static.nhtsa.gov/crashTest/images/2012/v07001P065.jpg
3rd rowhttps://static.nhtsa.gov/crashTest/images/2012/v07077P058.jpg
4th rowhttps://static.nhtsa.gov/crashTest/images/2012/v07719P002.jpg
5th rowhttps://static.nhtsa.gov/crashTest/images/2012/v07178P039.jpg
ValueCountFrequency (%)
https://static.nhtsa.gov/crashtest/images/2016/v08309p072.jpg 13
 
0.3%
https://static.nhtsa.gov/crashtest/images/2025/v08995p075.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2023/v08995p075.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2024/v08995p075.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2021/v08995p075.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2022/v08995p075.jpg 12
 
0.3%
https://static.nhtsa.gov/crashtest/images/2013/v07001p065.jpg 11
 
0.3%
https://static.nhtsa.gov/crashtest/images/2014/v07001p065.jpg 10
 
0.3%
https://static.nhtsa.gov/crashtest/images/2021/v11294p114.jpg 8
 
0.2%
https://static.nhtsa.gov/crashtest/images/2025/v11082p074.jpg 7
 
0.2%
Other values (2061) 3634
97.1%
2024-10-29T15:14:51.392549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 22458
 
9.8%
/ 22458
 
9.8%
t 22458
 
9.8%
a 14972
 
6.6%
0 12193
 
5.3%
h 11229
 
4.9%
. 11229
 
4.9%
g 10938
 
4.8%
2 8174
 
3.6%
v 7486
 
3.3%
Other values (22) 84728
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 137618
60.3%
Decimal Number 44916
 
19.7%
Other Punctuation 37430
 
16.4%
Uppercase Letter 8359
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 22458
16.3%
t 22458
16.3%
a 14972
10.9%
h 11229
8.2%
g 10938
7.9%
v 7486
 
5.4%
e 7486
 
5.4%
c 7486
 
5.4%
i 7486
 
5.4%
p 7195
 
5.2%
Other values (5) 18424
13.4%
Decimal Number
ValueCountFrequency (%)
0 12193
27.1%
2 8174
18.2%
1 6158
13.7%
7 5064
11.3%
4 2595
 
5.8%
9 2449
 
5.5%
5 2323
 
5.2%
3 2264
 
5.0%
8 2187
 
4.9%
6 1509
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
P 4034
48.3%
T 3743
44.8%
J 291
 
3.5%
G 291
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/ 22458
60.0%
. 11229
30.0%
: 3743
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 145977
63.9%
Common 82346
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 22458
15.4%
t 22458
15.4%
a 14972
10.3%
h 11229
7.7%
g 10938
7.5%
v 7486
 
5.1%
e 7486
 
5.1%
c 7486
 
5.1%
i 7486
 
5.1%
p 7195
 
4.9%
Other values (9) 26783
18.3%
Common
ValueCountFrequency (%)
/ 22458
27.3%
0 12193
14.8%
. 11229
13.6%
2 8174
 
9.9%
1 6158
 
7.5%
7 5064
 
6.1%
: 3743
 
4.5%
4 2595
 
3.2%
9 2449
 
3.0%
5 2323
 
2.8%
Other values (3) 5960
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 22458
 
9.8%
/ 22458
 
9.8%
t 22458
 
9.8%
a 14972
 
6.6%
0 12193
 
5.3%
h 11229
 
4.9%
. 11229
 
4.9%
g 10938
 
4.8%
2 8174
 
3.6%
v 7486
 
3.3%
Other values (22) 84728
37.1%

SidePoleVideo
Text

MISSING 

Distinct1993
Distinct (%)55.4%
Missing10790
Missing (%)75.0%
Memory size112.5 KiB
2024-10-29T15:14:51.528184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length61
Mean length61
Min length61

Characters and Unicode

Total characters219295
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique736 ?
Unique (%)20.5%

Sample

1st rowhttps://static.nhtsa.gov/crashTest/videos/2012/v07859C014.wmv
2nd rowhttps://static.nhtsa.gov/crashTest/videos/2012/v07001C014.wmv
3rd rowhttps://static.nhtsa.gov/crashTest/videos/2012/v07077C012.wmv
4th rowhttps://static.nhtsa.gov/crashTest/videos/2012/v07719C001.wmv
5th rowhttps://static.nhtsa.gov/crashTest/videos/2012/v07178C011.wmv
ValueCountFrequency (%)
https://static.nhtsa.gov/crashtest/videos/2016/v08309c014.wmv 13
 
0.4%
https://static.nhtsa.gov/crashtest/videos/2024/v08995c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2021/v08995c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2022/v08995c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2025/v08995c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2023/v08995c012.wmv 12
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2013/v07001c014.wmv 11
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2014/v07001c014.wmv 10
 
0.3%
https://static.nhtsa.gov/crashtest/videos/2021/v11294c013.mp4 8
 
0.2%
https://static.nhtsa.gov/crashtest/videos/2024/v11082c013.wmv 7
 
0.2%
Other values (1983) 3486
97.0%
2024-10-29T15:14:51.719126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 21570
 
9.8%
s 21570
 
9.8%
/ 21570
 
9.8%
v 14284
 
6.5%
0 11967
 
5.5%
h 10785
 
4.9%
a 10785
 
4.9%
. 10785
 
4.9%
1 8758
 
4.0%
2 7321
 
3.3%
Other values (21) 79900
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 132919
60.6%
Decimal Number 43236
 
19.7%
Other Punctuation 35950
 
16.4%
Uppercase Letter 7190
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 21570
16.2%
s 21570
16.2%
v 14284
10.7%
h 10785
8.1%
a 10785
8.1%
o 7190
 
5.4%
c 7190
 
5.4%
i 7190
 
5.4%
e 7190
 
5.4%
p 3691
 
2.8%
Other values (6) 21474
16.2%
Decimal Number
ValueCountFrequency (%)
0 11967
27.7%
1 8758
20.3%
2 7321
16.9%
3 2989
 
6.9%
4 2871
 
6.6%
9 2304
 
5.3%
8 2013
 
4.7%
5 1893
 
4.4%
7 1874
 
4.3%
6 1246
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 21570
60.0%
. 10785
30.0%
: 3595
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
C 3595
50.0%
T 3595
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 140109
63.9%
Common 79186
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 21570
15.4%
s 21570
15.4%
v 14284
10.2%
h 10785
 
7.7%
a 10785
 
7.7%
o 7190
 
5.1%
c 7190
 
5.1%
i 7190
 
5.1%
e 7190
 
5.1%
p 3691
 
2.6%
Other values (8) 28664
20.5%
Common
ValueCountFrequency (%)
/ 21570
27.2%
0 11967
15.1%
. 10785
13.6%
1 8758
11.1%
2 7321
 
9.2%
: 3595
 
4.5%
3 2989
 
3.8%
4 2871
 
3.6%
9 2304
 
2.9%
8 2013
 
2.5%
Other values (3) 5013
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 219295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 21570
 
9.8%
s 21570
 
9.8%
/ 21570
 
9.8%
v 14284
 
6.5%
0 11967
 
5.5%
h 10785
 
4.9%
a 10785
 
4.9%
. 10785
 
4.9%
1 8758
 
4.0%
2 7321
 
3.3%
Other values (21) 79900
36.4%

Interactions

2024-10-29T15:14:44.103131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:41.800530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.203618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.571981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.930765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.278499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.641112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.156709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:41.866584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.256686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.623785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.981275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.331117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.696906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.211559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:41.933725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.309771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.677493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.032385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.388546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.750944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.262857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:41.986842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.361015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.725485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.080182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.437653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.892492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.313262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.036412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.411838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.773684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.126179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.486042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.940976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.364151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.093849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.462630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.823141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.174149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.534153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.992920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.420933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.148175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.518006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:42.878317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.227090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:43.588084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-10-29T15:14:44.047014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-10-29T15:14:44.528543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-29T15:14:44.771537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-10-29T15:14:44.955841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

VehiclePictureOverallRatingOverallFrontCrashRatingFrontCrashDriversideRatingFrontCrashPassengersideRatingFrontCrashPictureFrontCrashVideoOverallSideCrashRatingSideCrashDriversideRatingSideCrashPassengersideRatingSideCrashVideocombinedSideBarrierAndPoleRating-FrontcombinedSideBarrierAndPoleRating-RearsideBarrierRating-OverallRolloverRatingRolloverRating2RolloverPossibilityRolloverPossibility2dynamicTipResultSidePoleCrashRatingNHTSAElectronicStabilityControlNHTSAForwardCollisionWarningNHTSALaneDepartureWarningComplaintsCountRecallsCountInvestigationCountModelYearMakeModelVehicleDescriptionVehicleIdSideCrashPictureSidePolePictureSidePoleVideo
0https://static.nhtsa.gov/images/vehicles/4447_st0640_046.pngNot RatedNot Rated54https://static.nhtsa.gov/crashTest/images/2008/05Matrix-f.jpghttps://static.nhtsa.gov/crashTest/videos/2008/05Matrix-f.wmvNot Rated54https://static.nhtsa.gov/crashTest/videos/2008/05Matrix-s.wmvNot RatedNot RatedNot RatedNot Rated40.0000.151Not RatedOptionalNoNo38202008TOYOTAMATRIX2008 Toyota Matrix 4-DR. w/SAB2500NoneNoneNone
1https://static.nhtsa.gov/images/vehicles/4637_st0640_046.pngNot RatedNot Rated44https://static.nhtsa.gov/crashTest/images/2008/06Prius-f.jpghttps://static.nhtsa.gov/crashTest/videos/2008/06Prius-f.wmvNot Rated54https://static.nhtsa.gov/crashTest/videos/2008/07Prius-s .wmvNot RatedNot RatedNot RatedNot Rated40.0000.130Not RatedOptionalNoNo1477422008TOYOTAPRIUS2008 Toyota Prius 4-DR.w/SAB2501https://static.nhtsa.gov/crashTest/images/2008/07Prius-s.jpgNoneNone
2https://static.nhtsa.gov/images/vehicles/5066_st0640_046.pngNot RatedNot Rated54https://static.nhtsa.gov/crashTest/images/2008/06Rav4-f.JPGhttps://static.nhtsa.gov/crashTest/videos/2008/06Rav4-f.wmvNot Rated55https://static.nhtsa.gov/crashTest/videos/2008/07RAV4-s.wmvNot RatedNot RatedNot Rated440.1740.179No TipNot RatedStandardNoNo5671442008TOYOTARAV42008 Toyota RAV4 4-DR. w/SAB2502https://static.nhtsa.gov/crashTest/images/2008/07RAV4-s.jpgNoneNone
3https://static.nhtsa.gov/images/vehicles/4638_st0640_046.pngNot RatedNot Rated45https://static.nhtsa.gov/crashTest/images/2008/05Sienna-f.jpghttps://static.nhtsa.gov/crashTest/videos/2008/05Sienna-f.wmvNot Rated55https://static.nhtsa.gov/crashTest/videos/2008/06Sienna-s.wmvNot RatedNot RatedNot Rated440.1690.159No TipNot RatedStandardNoNo424902008TOYOTASIENNA2008 Toyota Sienna w/SAB2503https://static.nhtsa.gov/crashTest/images/2008/06Sienna-s.jpgNoneNone
4https://static.nhtsa.gov/images/vehicles/5064_st0640_046.pngNot RatedNot Rated55https://static.nhtsa.gov/crashTest/images/2008/06Tacoma4-f.JPGhttps://static.nhtsa.gov/crashTest/videos/2008/06Tacoma4-f.wmvNot Rated55https://static.nhtsa.gov/crashTest/videos/2008/06Tacoma4-s.movNot RatedNot RatedNot Rated440.1910.147No TipNot RatedOptionalNoNo4271102008TOYOTATACOMA2008 Toyota Tacoma 4-DR.2504https://static.nhtsa.gov/crashTest/images/2008/06Tacoma4-s.JPGNoneNone
5https://static.nhtsa.gov/images/vehicles/4914_st0640_046.pngNot RatedNot Rated55https://static.nhtsa.gov/crashTest/images/2008/05Tacoma-f.jpghttps://static.nhtsa.gov/crashTest/videos/2008/05Tacoma-f.wmvNot Rated5Not RatedNoneNot RatedNot RatedNot Rated440.1910.147No TipNot RatedOptionalNoNo4271102008TOYOTATACOMA2008 Toyota Tacoma Extended Cab2505NoneNoneNone
6https://static.nhtsa.gov/images/vehicles/4912_st0640_046.pngNot RatedNot Rated55NoneNoneNot Rated5Not Ratedhttps://static.nhtsa.gov/crashTest/videos/2008/05Tacoma-s.wmvNot RatedNot RatedNot Rated440.1910.147No TipNot RatedOptionalNoNo4271102008TOYOTATACOMA2008 Toyota Tacoma Regular Cab2506https://static.nhtsa.gov/crashTest/images/2008/05Tacoma-s.jpgNoneNone
7https://static.nhtsa.gov/images/vehicles/4914_st0640_046.pngNot RatedNot Rated44NoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot Rated430.1980.204No TipNot RatedStandardNoNo3201302008TOYOTATUNDRA2008 Toyota Tundra Extended Cab w/SAB2507NoneNoneNone
8https://static.nhtsa.gov/images/vehicles/4346_st0640_046.pngNot RatedNot Rated44https://static.nhtsa.gov/crashTest/images/2008/07Tundra-f.JPGhttps://static.nhtsa.gov/crashTest/videos/2008/07Tundra-f.wmvNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot Rated430.1980.204No TipNot RatedStandardNoNo3201302008TOYOTATUNDRA2008 Toyota Tundra Regular Cab w/SAB2508NoneNoneNone
9https://static.nhtsa.gov/images/vehicles/4914_st0640_046.pngNot RatedNot Rated44https://static.nhtsa.gov/crashTest/images/2008/07Tundra4-f.jpghttps://static.nhtsa.gov/crashTest/videos/2008/07Tundra4-f.wmvNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot Rated430.1980.204No TipNot RatedStandardNoNo3201302008TOYOTATUNDRA2008 Toyota Tundra 4-DR. w/SAB2509NoneNoneNone
VehiclePictureOverallRatingOverallFrontCrashRatingFrontCrashDriversideRatingFrontCrashPassengersideRatingFrontCrashPictureFrontCrashVideoOverallSideCrashRatingSideCrashDriversideRatingSideCrashPassengersideRatingSideCrashVideocombinedSideBarrierAndPoleRating-FrontcombinedSideBarrierAndPoleRating-RearsideBarrierRating-OverallRolloverRatingRolloverRating2RolloverPossibilityRolloverPossibility2dynamicTipResultSidePoleCrashRatingNHTSAElectronicStabilityControlNHTSAForwardCollisionWarningNHTSALaneDepartureWarningComplaintsCountRecallsCountInvestigationCountModelYearMakeModelVehicleDescriptionVehicleIdSideCrashPictureSidePolePictureSidePoleVideo
14375NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardStandardStandard0002025NISSANARMADA2025 Nissan Armada SUV AWD20767NoneNoneNone
14376NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardStandardStandard0002025NISSANZ2025 Nissan Z 2 DR RWD20768NoneNoneNone
14377NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardStandardStandard0002025INFINITIQX802025 Infiniti QX80 SUV RWD20769NoneNoneNone
14378NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardStandardStandard0002025INFINITIQX802025 Infiniti QX80 SUV AWD20770NoneNoneNone
14379NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardNoNo0002025RIVIANR1T2025 Rivian R1T PU/CC AWD20771NoneNoneNone
14380NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardNoNo0002025RIVIANR1S2025 Rivian R1S SUV AWD20772NoneNoneNone
14381NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardNoNo0002025RIVIANEDV 7002025 Rivian EDV 700 CV FWD20773NoneNoneNone
14382NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardNoNo0002025RIVIANEDV 5002025 Rivian EDV 500 CV FWD20774NoneNoneNone
14383NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardNoNo0002025RIVIANRCV-DELIVERY 5002025 Rivian RCV-Delivery 500 CV FWD20775NoneNoneNone
14384NoneNot RatedNot RatedNot RatedNot RatedNoneNoneNot RatedNot RatedNot RatedNoneNot RatedNot RatedNot RatedNot RatedNot Rated0.00.0Not RatedStandardNoNo0002025RIVIANRCV-DELIVERY 7002025 Rivian RCV-Delivery 700 CV FWD20776NoneNoneNone